**2.4 Biological control**

Biological control is the use of natural enemies to manage pests' populations. Natural enemies are very important agents in reducing or regulating populations of pests and include parasitoids, predators and pathogens. A parasitoid is an organism that spends its larval stage in or on another organism, also known as a host. The larval parasitoid feeds only on the host as it develops, eventually killing the host. There are no report of mite's parasitoids. Predators are free living organisms, each of which will consume a number of pests (prey) in their lifespan. More than 65 predators have been recorded for European red mite, *Panonychus ulmi* (Koch), alone. Among the more important of these biological agents are predatory mites and insects, but others include spiders and disease-producing pathogens [3]. Three major methods exist for the use of natural enemies: conservation, classical biological control and augmentation.

Conservation seeks to identify and rectify negative influences of human activities that suppress natural enemies and to enhance agricultural fields as habitats for natural enemies. In conservation, the assumption is that the species of natural enemies already exist locally and have potential to effectively control the pest if given an opportunity to do so [18]. Classical biological control involves importation, evaluation, release and permanent establishment of natural enemies in the environment from the area of origin of a foreign pest. It assume that natural enemies from the area of the pest's origin will be more effective than natural enemies in the pest's new environment [9]. Augmentation involves the mass rearing and release of natural enemies to control target pest. The natural enemies must be capable of being mass reared and must be released at an appropriate time and in sufficient number to be effective. Two approaches are taken in augmentation. Inoculation involves releasing small number of natural enemies early in crop cycle with the expectation that they will reproduce and their offspring will provide pest control for an extended period of time. Inundation involves releasing large number of natural enemies for immediate control of pest when insufficient reproduction of the released natural enemies is likely to occur [18].

We found predatory mites from families Phytoseiidae, Ameroseiidae, Parasitidae, Stigmaeidae, Anystidae and Bdellidae as natural enemies of Tetranychidae during our sampling from Northwestern Iran (2007–2008). Among predator insects, we found *Stethorus gilvifrons* Mulsant (Col.: Coccinellidae), *Oenopia conglobata* (Linnaeus) (Col.: Coccinellidae), *Exochomus quadripustulatus* (Linnaeus) (Col.: Coccinellidae), *Chrysoperla carnea* (Stephens) (Neuroptera: Chrysopidae), *Scolothrips* sp. (Thysanoptera: Thripidae) and *Orius horvathi* Reuter (Het.: Anthocoridae). Among the predatory mites that we found, here we describe, *Phytoseius plumifer* (Acari: Phytoseiidae), which we have been worked on it.

Predaceous mites of the family Phytoseiidae are important natural enemies of several phytophagous mites and other pests on various crops. Phytoseiid mites occur throughout the world. Several authors have considered *Phytoseius plumifer* among the most important predators of phytophagous mites infesting fruit trees [19]. Before using natural enemies in biological control programs, it is essential to evaluate their efficiency and therefore, knowledge of the behavioral attributes of *P. plumifer* is essential for understanding the efficiency of this predator in the biological control of two-spotted spider mite.

### *2.4.1 Prey stage preference, switching and mutual interference of* Phytoseius plumifer

Prey stage preference may affect prey–predator population dynamics, if the prey stage affects the development and reproduction of the predator. Prey preference by biological control agents can affect their ability to effectively control target pests too [20]. Preference may vary with the relative abundance of two prey types, in which case if the predator or parasitoid eats or oviposits in disproportionately more of the more abundant type, it is said to display switching behavior. In other words, switching is a behavioral phenomenon whereby a predator alters its preference for the prey species or type as prey relative densities change [21]. Murdoch et al. [22] found that switching could result from several different mechanisms including when (1) the predator develops a search image for the prey type with the highest relative abundance, (2) capture success on a prey type increases with increase in its relative abundance and (3) when the predator's habitat contains sub-habitats that are occupied by different prey types.

Aggregation of predators in space to prey patches causes the prey–predator interaction occur and searching efficiency to decrease with increasing predator density. Inverse density dependence in searching efficiency is known as predator interference or mutual interference. However, it was found that increasing the number of biological control agents released into an environment did not always increase the level of pest control [23]. This occurs when parasites/predators that are searching for a host/prey encounter each other, which can cause one or both to stop searching and possibly leave the area [24].

In our previous work we determined some aspects of the behavioral characteristics of *P. plumifer* on the two-spotted spider mite. We studied the preference of *P. plumifer* for different life stages of the two-spotted spider mite under choice and no-choice conditions. Switching of *P. plumifer* was tested with deutonymphs and larvae of the prey with different ratios too. Also, since the success of a predator in biological control programs is dependent on its behavior under the presence of other con-specific individuals, we investigated the mutual interference of *P. plumifer* in different densities of predator mites [25].

*Biological Control of Tetranychidae by Considering the Effect of Insecticides DOI: http://dx.doi.org/10.5772/intechopen.100296*

#### *2.4.1.1 Materials and methods*

#### *2.4.1.1.1 No-choice experiment*

In the feeding tests, we offered a total of 30 prey individuals of egg, larva, protonymph, deutonymph, male and female separately to a 24 h starved unmated female predator on soybean leaf arena and then allowed each predator to feed on the prey individuals for a total of 24 h. At the end of the experiment we estimated the number of prey individuals consumed per predator on each life stage of the prey.

#### *2.4.1.1.2 Choice experiment*

In this experiment we exposed total of 30 prey items i.e. equal number (5) of all stages of *T. urticae* (egg, larva, protonymph, deutonymph, male and female) to the predator females.

#### *2.4.1.1.3 Switching*

Switching of *P. plumifer* was tested with deutonymphs and larvae of the prey. Deutonymphs (D) and larvae (L) of *T. urticae* were presented in five different ratio treatments: 30 L:70D, 40 L:60D, 50 L:50D, 60 L:40D and 70 L:30D. The total prey number was 30. For evaluating the value of selectivity the following equation were used:

$$\mathbf{C} = \mathbf{E}\_1 / \mathbf{E}\_2 \tag{1}$$

where *E*1 and *E*2 are the proportion of larvae and deutonymphs killed in 50 L:50D ratio, respectively. To find the expected ratio of killed larvae and deutonymphs in no-choice position the obtained data were analyzed by Murdoch [22] formula as follow:

$$Y = \mathbb{C}\_{\times} \left/ \left( \mathbb{1} - X + \mathbb{C}\_{\times} \right) \right. \tag{2}$$

where *C*x is *C*× ratio of stage and *X* is the ratio of a prey stage on a leaf disc.

#### *2.4.1.1.4 Mutual interference*

In this experiment, 160 immature individuals (larvae and protonymphs) of *T. urticae* were placed on each leaf arena. In the next step, female predators at densities of 1, 2, 4, 8 and 16 per leaf arena were allowed to search the prey for 24 h. After this time period, the predators were removed from the arena and the number of eaten preys was counted. Finally, the per capita searching efficiency (*a*) of the predator at different densities was calculated according to the Nicholson [26] equation as follows:

$$\mathbf{a} = \left(\mathbf{1} / \text{PT}\right) \ln\left(\mathbf{N}\_{\text{t}} / \left(\mathbf{N}\_{\text{t}} - \mathbf{N}\_{\text{a}}\right)\right) \tag{3}$$

where *N*t is the total number of available prey (160), Na is the total number of eaten preys, *P* is the number of predators, and *T* is the duration of the experiment (set to 1.0 for one day).

The calculated searching efficiency (*a*) was fitted against predator density (both on a logarithmic scale). The points were fitted to a linear regression by the least square method, according to the inductive model given by Hassell and Varley [27] as follows:

$$\mathbf{a} = \mathbf{Q} \mathbf{P}^{-m} \text{ or } \log \mathbf{a} = \log \mathbf{Q} - \mathbf{m} \log \mathbf{P} \tag{4}$$

where a is the searching efficiency of the predators, *Q* is the quest constant, and m includes only the component of interference due to behavioral interactions between predators [28].

#### *2.4.1.2 Results*

Our results indicated that in our no-choice preference experiments the predation preference of this predator on the different stages of *T. urticae* was as follow: eggs >protonymphs>larvae>males>deutonymphs>females of *T. urticae*. The preferred stage of two-spotted spider mite in choice preference experiments was protonymph. There was no tendency to the adult females of *T. urticae* in our results maybe because of their big size and the feeding rate was zero. Females of the predator killed more larvae than deutonymphs in switching experiments and they preferred larval stage compared to deutonymphs. There was positive switching behavior of predator for larval stage of prey at all ratios except 40%Larva: 60%Deutonymph (**Figure 1**) maybe because of their smaller size.

The values of total predation rate of *P. plumifer* were significantly different at different densities of the predator and the highest and lowest values of this parameter were recorded at 16 and 1 density of this predator, respectively. Furthermore, the per capita predation rate decreased to 1/4 with increasing the predator density from 1 to 16 and consequently the per capita searching efficiency also decreased significantly. According to results of Murdoch et al. [22] mechanisms one and two appear likely for our predator and capture increases on a prey type with increasing in its relative abundance.

The linear relationship between the natural logarithm of the predator density and the natural logarithm of per capita searching efficiency in mutual interference analysis has been demonstrated a negative slope. The negative value of the

#### **Figure 1.**

*Switching behavior of* Phytoseius plumifer *females to different ratios of larval stage and deutonymph of*  Tetranychus urticae.

#### *Biological Control of Tetranychidae by Considering the Effect of Insecticides DOI: http://dx.doi.org/10.5772/intechopen.100296*

interference coefficient in the mutual interference analysis showed an inverse relationship between the predator density and per capita searching efficiency and this fact revealed that the searching efficiency of *P. plumifer* significantly decreased with increasing predator density as a result of mutual interference. For most augmentative biological control agents, there is an optimal release rate that produces effective control of a pest species. Increasing the release rate above the optimal rate does not improve the control of pest species and is potentially economically detrimental [29]. In our study although with an increasing number of predators, greater numbers of preys have been consumed but, a doubling in the number of predator employed for *T. urticae* predation did not result in a doubling in the number of mite consumed, because of mutual interference. A significant decrease of the number of prey consumed per predator with an increased predator density suggests that interference among predators also increase at higher predator density. This is probably due to a closed experimental arena with limited predation time and high probability of mutual interference. However, under field conditions, factors such as large searching areas, the effects of other predator species, spatial complexity, and weather may affect the effectiveness of natural enemies [30].
